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DBMS > AnzoGraph DB vs. GridGain vs. Netezza vs. Sadas Engine vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. GridGain vs. Netezza vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGridGain  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationGridGain is an in-memory computing platform, built on Apache IgniteData warehouse and analytics appliance part of IBM PureSystemsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.gridgain.comwww.ibm.com/­products/­netezzawww.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.gridgain.com/­docs/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCambridge SemanticsGridGain Systems, Inc.IBMSADAS s.r.l.Apache Software Foundation
Initial release20182007200020062014
Current release2.3, January 2021GridGain 8.5.18.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++Scala
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux infoincluded in applianceAIX
Linux
Windows
Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesnono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.ANSI-99 for query and DML statements, subset of DDLyesyesSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesC++
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yesnono
Triggersnoyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes (replicated cache)Source-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users and rolesSecurity Hooks for custom implementationsUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standardno

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More resources
AnzoGraph DBGridGainNetezza infoAlso called PureData System for Analytics by IBMSadas EngineSpark SQL
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